code: def testBroadcastToShapeTypeAndInference(self):
      for dtype in [dtypes.int32, dtypes.int64]:
          with self.cached_session():
              x = np.array([1, 2, 3])
              v_tf = array_ops.broadcast_to(
                  constant_op.constant(x),
                  constant_op.constant([3, 3], dtype=dtype),
              )
              shape = v_tf.get_shape().as_list()
              v_np = np.broadcast_to(x, [3, 3])
              self.assertAllEqual(v_tf, v_np)
              # check shape inference when shape input is constant
              self.assertAllEqual(shape, v_np.shape)
  
imports: import numpy
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.platform import test
label_desc: Use image node_id 10 for calling the BroadcastToTest obj's underlying member method code with example usage: obj.testBroadcastToShapeTypeAndInference() without return types